| Description |
1 online resource : illustrations (colour) |
| Summary |
This dataset example introduces readers to ordered probit. This technique allows researchers to evaluate whether a categorical variable with three or more categories that follow some order is a function of one or more independent variables. The ordered probit model is most commonly estimated via maximum likelihood estimation (MLE). This example uses a subset of data from the 2013 Behavioral Risk Factor Surveillance System (BRFSS) operated by the U.S. Centers for Disease Control. It presents an analysis of the strenuousness of the exercise activities someone engaged in during the previous 30 days as a function of their gender, age, income, and education level. An analysis like this allows researchers to evaluate factors that predict activity levels, which may be useful in designing fitness plans |
| Bibliography |
Includes bibliographical references |
| Audience |
Specialized |
| Notes |
Description based on online resource; title from home page (viewed on January 8, 2016) |
| Subject |
Probits.
|
|
Research -- Statistical methods.
|
|
Research -- Statistical methods -- Case studies.
|
|
Exercise -- United States -- Statistics.
|
| Genre/Form |
Case studies.
|
|
Statistics.
|
| Form |
Electronic book
|
| Author |
The Odum Institute, host institution
|
| ISBN |
9781473961975 (online resource) |
|
1473961971 |
|
